![]() ![]() SELECT Name, City, Country FROM dbo.Customers_2 SELECT Name, City, Country FROM dbo.Customers_1 But, with the help of the UNION ALL operator, we can even combine duplicate entries of multiple SELECT statements within a single view. Generally, a simple view in SQL Server includes the use of a single select statement. Similar to UNION operator in a SQL Server VIEW, using UNION ALL is also quite simple. Now that we have a clear idea of how to use the UNION operator in a SQL Server View, let’s understand how to use the UNION ALL operator in a view. Read How to view table in SQL Server How to use union all in view SQL Server So, the view will return the distinct city names from both the tables that come under the United States. Moreover, we are also using a WHERE clause with each SELECT statement to fetch records where the country is the United States. And in the definition, we are using 2 SELECT statements to fetch the city and country columns from respective tables. In the above example, we have created a view with the name US_CityView. SELECT City, Country FROM dbo.Customers_2 SELECT City, Country FROM dbo.Customers_1 And again for this example, we will use the same tables illustrated in the previous section. Let’s understand the whole implementation using an example. But, with the help of the UNION operator, we can combine the results of multiple SELECT statements within a single view. So, using a UNION operator in a SQL Server VIEW is quite simple. Now that we have a clear idea about the use of the UNION operator, let’s understand how to use it in a view in SQL Server. Read SQL Server view order by How to use union in view SQL Server Now, from the above outputs, we can easily understand the difference between UNION and UNION ALL operators. Let’s understand the syntax of using the UNION and UNION ALL operator in SQL Server. A UNION operator in SQL Server does not include duplicate entries, while the UNION ALL operator includes duplicates in the result. ![]() Now, there is a slight difference between a UNION and a UNION ALL operator in SQL Server. As the name specifies, the main aim of the UNION operator is to perform the UNION operation. In SQL Server, the UNION operator is used to perform a set operation of combining the results of multiple SELECT queries. Read Create a table from view in SQL Server Union & Union All in SQL Server Moreover, we can also specify any sort of condition with the SELECT statement. After this, we can use the SELECT statement to fetch some columns from a table. ![]() Now, after CREATE VIEW keyword, we have to specify the name of the view instead of view_name.In the syntax, we are using the CREATE VIEW statement to create a simple user-defined view in SQL Server.In this section, we will only cover the syntax of creating a view in SQL Server. For more information, refer to “ View in SQL Server“. A view includes a set of SQL queries for retrieving data from the database. In SQL Server, a VIEW is just like a virtual table that holds data from one or more than one table. How to use union all in view SQL Server.But, in the "fog of war" on a Zoom call with several other people watching me live-type SQL, this felt like the right approach. Isn't SQL just thrilling?! I am sure there are good number of ways to accomplish what I demonstrated. Woot woot! As you can see, by merging the CSV data and the friend table in a single SQL query, I was able to pull in the friend.name column in order to augment the existing CSV column data. | 5 | Sandi | Vegan, Multi-Grain Pancakes | > ( SELECT 5 AS id, "Vegan, Multi-Grain Pancakes" AS favoriteMeal ) > ( SELECT 4 AS id, "Bella's Chicken Burrito" AS favoriteMeal ) UNION ALL > ( SELECT 1 AS id, "Pizza" AS favoriteMeal ) UNION ALL Imagine that I had a database table called friend with the following structure: That said, let's paint a picture of what was going on. Given the relatively small size of the CSV payload, what follows just felt like the appropriate level of effort. As such, I couldn't load the CSV file into a "real table". But, I was working with a database in which I had read only permissions. To be clear, this is not the only way to consume CSV data in a relational database. ![]() The CSV file was fairly small so, I ended up using the awesome power of multiple-cursors in SublimeText 3 in order to write a SQL query that converted the CSV data into a derived table that I then consumed in an INNER JOIN in MySQL. Yesterday, when working with some data scientists, I had to merge a few columns from a database table into a CSV (Comma-Separated Values) file that the data scientists had created. I've been writing web-applications on top of relational databases (RDBMS) for a while and, SQL always feels like a luxurious combination of structure and flexibility. ![]()
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